There are a number of ways of comparing images. Furthermore, there are many different implementations of comparing images. One implementation is to search based on the content of the image rather than a keyword.
A content based image retrieval system is an image retrieval system which classifies, detects and retrieves images from digital libraries, usually databases, by utilizing the content of the image rather than a text label.
Conventional content based image and video retrieval systems utilize images or video frames which have been supplemented with text such as titles, keywords or captions associated with the images. A user retrieves desired images from an image database, for example, by submitting textual queries to the system using these keywords. Images that match the input keywords are retrieved. However, with larger sets of image data, it becomes impractical to store all of the images with text indexes corresponding to each image. It is also highly burdensome for someone to manually attribute specific titles, keywords and captions to each one. Furthermore, text-based searches have their inherent drawbacks as well.
Some content based systems retrieve images using a specified shape or object. For example, to find images of a dog, such systems would be provided with a specification of a shape of a dog. However, since dogs come in a variety of shapes and sizes, this is limited to only finding dogs that match the designated shapes.